Major Extracranial Injury Research Articles

Association of early blood-based biomarkers and six-month functional outcomes in conventional severity categories of traumatic brain injury: capturing the continuous spectrum of injury

Traumatic brain injury is conventionally categorised as mild, moderate, or severe on the Glasgow Coma Scale (GCS). Recently developed biomarkers can provide more objective and nuanced measures of the extent of brain injury. Exposure-response relationships were investigated in 2479 patients aged ≥16 enrolled in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) prospective observational cohort study. Neurofilament protein-light (NFL), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and glial fibrillary acidic protein (GFAP) were assayed from serum sampled in the first 24h; concentrations were divided into quintiles within GCS severity groups. Relationships with the Glasgow Outcome Scale-Extended were examined using modified Poisson regression including age, sex, major extracranial injury, time to sample, and log biomarker concentration as covariates. Within severity groups there were associations between biomarkers and outcomes after adjustment for covariates: GCS 13-15 and negative CT imaging (relative risks [RRs] from 1.28 to 3.72), GCS 13-15 and positive CT (1.21-2.81), GCS 9-12 (1.16-2.02), GCS 3-8 (1.09-1.94). RRs were associated with clinically important differences in expectations of prognosis. In patients with GCS 3 (RRs 1.51-1.80) percentages of unfavourable outcome were 37-51% in the lowest quintiles of biomarker levels and reached 90-94% in the highest quintiles. Similarly, for GCS 15 (RRs 1.83-3.79), the percentages were 2-4% and 19-28% in the lowest and highest biomarker quintiles, respectively. Conventional TBI severity classification is inadequate and underestimates heterogeneity of brain injury and associated outcomes. The adoption of circulating biomarkers can add to clinical assessment of injury severity. European Union 7th Framework program (EC grant 602150), Hannelore Kohl Stiftung, One Mind, Integra LifeSciences, Neuro-Trauma Sciences, NIHR Rosetrees Trust.

Contrasting Characteristics and Outcomes of Sports-Related and Non–Sports-Related Traumatic Brain Injury

Exposure to traumatic brain injury (TBI) has raised widespread concern over participation in sports, particularly over possible long-term consequences. However, little is known about the outcomes of individuals presenting to hospitals with sports-related TBI. To compare the characteristics and outcomes of individuals presenting to hospitals with sports-related and non-sports-related TBI. The CENTER-TBI (Collaborative European NeuroTrauma Effectiveness Research in TBI) observational cohort study was conducted at hospitals in 18 countries. The study enrolled 4509 patients who had TBI and had an indication for computed tomography (CT), of whom 4360 were 16 years or older. Outcomes were assessed at 3 and 6 months, and groups were compared using regression analyses adjusting for clinical and demographic differences. Data were collected between December 9, 2014, and December 17, 2017, and analyzed from August 2022 to March 2023. Sports-related and non-sports-related TBI with subgroups selected by severity of injury. The main outcome was the Glasgow Outcome Scale-Extended (GOSE) at 6 months, with secondary outcomes covering postconcussion symptoms, health-related quality of life, and mental health. A total of 4360 patients were studied, including 256 (6%) with sports-related TBI (mean [SD] age, 38.9 [18.1] years; 161 [63%] male) and 4104 with non-sports-related TBI (mean [SD] age, 51.0 [20.2] years; 2773 [68%] male). Compared with patients with non-sports-related TBI, patients with sports-related TBI were younger, more likely to have tertiary education, more likely to be previously healthy, and less likely to have a major extracranial injury. After adjustment, the groups did not differ in incomplete recovery (GOSE scores <8) at 6 months (odds ratio [OR], 1.27; 95% CI, 0.90-1.78; P = .22 for all patients; OR, 1.20; 95% CI, 0.83-1.73; P = .34 for those with mild TBI; and OR, 1.19; 95% CI, 0.74-1.92; P = .65 for those with mild TBI and negative CT findings). At 6 months, there was incomplete recovery in 103 of 223 patients (46%) with outcomes in the sports-related TBI group, 65 of 168 (39%) in those with mild sports-related TBI, and 30 of 98 (31%) in those with mild sports-related TBI and negative CT findings. In contrast, at 6 months, the sports-related TBI group had lower prevalence of anxiety, depression, posttraumatic stress disorder, and postconcussion symptoms than the non-sports-related group. In this cohort study of 4360 patients with TBI, functional limitations 6 months after injury were common after sports-related TBI, even mild sports-related TBI. Persisting impairment was evident in the sports-related TBI group despite better recovery compared with non-sports-related TBI on measures of mental health and postconcussion symptoms. These findings caution against taking an overoptimistic view of outcomes after sports-related TBI, even if the initial injury appears mild.

Acute Extra-Arachnoid Subdural Hematomas in Patients 50 Years and Older: When Subdurals Act Like Epidurals

Some patients with subdural hematoma (SDH) with acute extra-arachnoid lesions and without concomitant subarachnoid blood or contusions may present in similarly grave neurological condition compared with the general population of patients with SDH. However, these patients often make an impressive neurological recovery. This study compared neurological outcomes in patients with extra-arachnoid SDH with all other SDH patients. We compared a prospective series of extra-arachnoid SDH patients without subarachnoid hemorrhage or other concomitant intracranial injury with a Transforming Research and Clinical Knowledge in TBI control group with SDH only. We performed inverse probability weighting for key characteristics and ordinal regression with and without controlling for midline shift comparing neurological outcomes (Extended Glasgow Outcome Scale score) at 2 weeks. We used the Corticosteroid Randomization After Significant Head Injury prognostic model to predict mortality based on age, Glasgow Coma Scale score, pupil reactivity, and major extracranial injury. Mean midline shift was significantly different between extra-arachnoid SDH and control groups (7.2 mm vs. 2.7 mm, P < 0.001). After weighting for group allocation and controlling for midline shift, extra-arachnoid SDH patients had 5.68 greater odds (P < 0.001) of a better 2-week Extended Glasgow Outcome Scale score than control patients. Mortality in the extra-arachnoid SDH group was less than predicted by the Corticosteroid Randomization After Significant Head Injury prognostic model (10% vs. 21% predicted). Patients with extra-arachnoid SDH have significantly better 2-week neurological outcomes and lower mortality than predicted by the Corticosteroid Randomization After Significant Head Injury model. Neurosurgeons should consider surgery for this patient subset even in cases of poor neurological examination, older age, and large hematoma with high degree of midline shift.

Development of prognostic models for Health-Related Quality of Life following traumatic brain injury

BackgroundTraumatic brain injury (TBI) is a leading cause of impairments affecting Health-Related Quality of Life (HRQoL). We aimed to identify predictors of and develop prognostic models for HRQoL following TBI.MethodsWe used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Core study, including patients with a clinical diagnosis of TBI and an indication for computed tomography presenting within 24 h of injury. The primary outcome measures were the SF-36v2 physical (PCS) and mental (MCS) health component summary scores and the Quality of Life after Traumatic Brain Injury (QOLIBRI) total score 6 months post injury. We considered 16 patient and injury characteristics in linear regression analyses. Model performance was expressed as proportion of variance explained (R2) and corrected for optimism with bootstrap procedures.Results2666 Adult patients completed the HRQoL questionnaires. Most were mild TBI patients (74%). The strongest predictors for PCS were Glasgow Coma Scale, major extracranial injury, and pre-injury health status, while MCS and QOLIBRI were mainly related to pre-injury mental health problems, level of education, and type of employment. R2 of the full models was 19% for PCS, 9% for MCS, and 13% for the QOLIBRI. In a subset of patients following predominantly mild TBI (N = 436), including 2 week HRQoL assessment improved model performance substantially (R2 PCS 15% to 37%, MCS 12% to 36%, and QOLIBRI 10% to 48%).ConclusionMedical and injury-related characteristics are of greatest importance for the prediction of PCS, whereas patient-related characteristics are more important for the prediction of MCS and the QOLIBRI following TBI.

Association of Early Multiple Organ Dysfunction With Clinical and Functional Outcomes Over the Year Following Traumatic Brain Injury: A Transforming Research and Clinical Knowledge in Traumatic Brain Injury Study.

Traumatic brain injury is a leading cause of death and disability in the United States. While the impact of early multiple organ dysfunction syndrome has been studied in many critical care paradigms, the clinical impact of early multiple organ dysfunction syndrome in traumatic brain injury is poorly understood. We examined the incidence and impact of early multiple organ dysfunction syndrome on clinical, functional, and disability outcomes over the year following traumatic brain injury. Retrospective cohort study. Patients enrolled in the Transforming Clinical Research and Knowledge in Traumatic Brain Injury study, an 18-center prospective cohort study of traumatic brain injury patients evaluated in participating level 1 trauma centers. Adult (age > 17 yr) patients with moderate-severe traumatic brain injury (Glasgow Coma Scale < 13). We excluded patients with major extracranial injury (Abbreviated Injury Scale score ≥ 3). Development of early multiple organ dysfunction syndrome, defined as a maximum modified Sequential Organ Failure Assessment score greater than 7 during the initial 72 hours following admission. The main outcomes were: hospital mortality, length of stay, 6-month functional and disability domains (Glasgow Outcome Scale-Extended and Disability Rating Scale), and 1-year mortality. Secondary outcomes included: ICU length of stay, 3-month Glasgow Outcome Scale-Extended, 3-month Disability Rating Scale, 1-year Glasgow Outcome Scale-Extended, and 1-year Disability Rating Scale. We examined 373 subjects with moderate-severe traumatic brain injury. The mean (sd) Glasgow Coma Scale in the emergency department was 5.8 (3.2), with 280 subjects (75%) classified as severe traumatic brain injury (Glasgow Coma Scale 3-8). Among subjects with moderate-severe traumatic brain injury, 252 (68%) developed early multiple organ dysfunction syndrome. Subjects that developed early multiple organ dysfunction syndrome had a 75% decreased odds of a favorable outcome (Glasgow Outcome Scale-Extended 5-8) at 6 months (adjusted odds ratio, 0.25; 95% CI, 0.12-0.51) and increased disability (higher Disability Rating Scale score) at 6 months (adjusted mean difference, 2.04; 95% CI, 0.92-3.17). Subjects that developed early multiple organ dysfunction syndrome experienced an increased hospital length of stay (adjusted mean difference, 11.4 d; 95% CI, 7.1-15.8), with a nonsignificantly decreased survival to hospital discharge (odds ratio, 0.47; 95% CI, 0.18-1.2). Early multiple organ dysfunction following moderate-severe traumatic brain injury is common and independently impacts multiple domains (mortality, function, and disability) over the year following injury. Further research is necessary to understand underlying mechanisms, improve early recognition, and optimize management strategies.

Prehospital Management of Traumatic Brain Injury across Europe: A CENTER-TBI Study

Background Prehospital care for traumatic brain injury (TBI) is important to prevent secondary brain injury. We aim to compare prehospital care systems within Europe and investigate the association of system characteristics with the stability of patients at hospital arrival. Methods We studied TBI patients who were transported to CENTER-TBI centers, a pan-European, prospective TBI cohort study, by emergency medical services between 2014 and 2017. The association of demographic factors, injury severity, situational factors, and interventions associated with on-scene time was assessed using linear regression. We used mixed effects models to investigate the case mix adjusted variation between countries in prehospital times and interventions. The case mix adjusted impact of on-scene time and interventions on hypoxia (oxygen saturation <90%) and hypotension (systolic blood pressure <100mmHg) at hospital arrival was analyzed with logistic regression. Results Among 3878 patients, the greatest driver of longer on-scene time was intubation (+8.3 min, 95% CI: 5.6–11.1). Secondary referral was associated with shorter on-scene time (-5.0 min 95% CI: −6.2– −3.8). Between countries, there was a large variation in response (range: 12–25 min), on-scene (range: 16-36 min) and travel time (range: 15–32 min) and in prehospital interventions. These variations were not explained by patient factors such as conscious level or severity of injury (expected OR between countries: 1.8 for intubation, 1.8 for IV fluids, 2.0 for helicopter). On-scene time was not associated with the regional EMS policy (p= 0.58). Hypotension and/or hypoxia were seen in 180 (6%) and 97 (3%) patients in the overall cohort and in 13% and 7% of patients with severe TBI (GCS <8). The largest association with secondary insults at hospital arrival was with major extracranial injury: the OR was 3.6 (95% CI: 2.6–5.0) for hypotension and 4.4 (95% CI: 2.9–6.7) for hypoxia. Discussion Hypoxia and hypotension continue to occur in patients who suffer a TBI, and remain relatively common in severe TBI. Substantial variation in prehospital care exists for patients after TBI in Europe, which is only partially explained by patient factors.

Surgery for acute subdural hematoma: the value of pre-emptive decompressive craniectomy by propensity score analysis.

Acute subdural hematomas (ASDH) are found frequently following traumatic brain injury (TBI) and they are considered the most lethal type of mass lesions. The decision to perform a procedure to evacuate ASDH and the approach, either via craniotomy or decompressive craniectomy (DC), remains controversial. We reviewed a prospectively collected series of 343 moderate to severe TBI patients in whom ASDH was the main lesion (ASDH volumes ≥10 cc). Patients with early comfort measures (early mortality prediction >50% and not ICP monitored), bilateral ASDH or the presence of another intracranial hematoma with volumes exceeding two times the volume of the ASDH were excluded. Among them, 112 were managed conservatively, 65 underwent ASDH evacuation by craniotomy and 166 by DC (103 pre-emptive DC, 63 obligatory DC). We calculated the average treatment effect by propensity score (PS) analysis using the following covariates: age, year, hypoxia, shock, pupils, major extracranial injury, motor score, midline shift, ASDH volume, swelling, intraventricular and subarachnoid hemorrhage presence. Then, multivariable binary regression and ordinal logistic regression analysis were performed to estimate associations between predictors and mortality and 12 months-GOS respectively. The patients' inverse probability weights were included as an independent variable in both regression models. The main variables associated with outcome were year, age, falls from patient´s own height, hypoxia, early deterioration, pupillary abnormalities, basal cistern effacement, compliance to ICP monitoring guidelines and type of surgical approach (craniotomy and pre-emptive DC). According to sliding dichotomy analysis, we found that patients in the intermediate or worst bands of unfavorable outcome prognosis seemed to achieve better than expected outcome if they underwent pre-emptive DC rather than craniotomy.

The Utility of the Modified Frailty Index in Outcome Prediction for Elderly Patients with Acute Traumatic Subdural Hematoma.

This study aimed to evaluate the utility of the 11-variable modified Frailty Index (mFI) in prognosticating elderly patients with traumatic acute subdural hematomas (aSDHs). A state-service level 1 trauma center registry was interrogated to investigate consecutive patients ≥65 years of age presenting with traumatic aSDH, with or without major extracranial injury, between January 2013 and December 2017. mFI on admission, demographics, and admission details, including Glasgow Coma Scale (GCS) and pupillary status and radiological findings, were retrospectively retrieved from institutional records. Clinical outcome data were retrieved from medical records and the Victorian State Trauma Registry (VSTR). Outcome measures were 1) 30-day mortality and 2) 6-month unfavorable outcome, defined by the Extended Glasgow Outcome Scale (GOS-E). Five hundred twenty-nine consecutive cases were identified from the registry. Demographic data included: 1) age (median; interquartile range) = 80.46; 74.17-85.89; 2) mFI (mean ± standard deviation) = 1.96 ± 1.42 of 11 variables. Four hundred sixteen cases (79%) had complete outcome data. As mFI increased from 0/11 variables to ≥5/11 variables (≥0.45), 30-day mortality risk increased from 17.72% to 39.29% (p = 0.023) and 6-month unfavorable outcome risk increased from 40.51% to 96.43% (p < 0.001). Multi-variate analysis showed that greater mFI score of ≥3/11 variables (≥0.27) suggested a significantly higher risk of 30-day mortality (p = 0.009) and unfavorable outcome (p < 0.001). We conclude that increasing frailty, as measured by the mFI, was associated with significantly higher risk of 30-day mortality and 6-month unfavorable outcome in elderly patients presenting with aSDH to a level 1 neurotrauma center. Assessment of mFI in elderly patients with aSDH may be a useful determinant of outcome for this rapidly growing population.

Toward a New Multi-Dimensional Classification of Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research for Traumatic Brain Injury Study.

Traumatic brain injury (TBI) is currently classified as mild, moderate, or severe TBI by trichotomizing the Glasgow Coma Scale (GCS). We aimed to explore directions for a more refined multidimensional classification system. For that purpose, we performed a hypothesis-free cluster analysis in the Collaborative European NeuroTrauma Effectiveness Research for TBI (CENTER-TBI) database: a European all-severity TBI cohort (n = 4509). The first building block consisted of key imaging characteristics, summarized using principal component analysis from 12 imaging characteristics. The other building blocks were demographics, clinical severity, secondary insults, and cause of injury. With these building blocks, the patients were clustered into four groups. We applied bootstrap resampling with replacement to study the stability of cluster allocation. The characteristics that predominantly defined the clusters were injury cause, major extracranial injury, and GCS. The clusters consisted of 1451, 1534, 1006, and 518 patients, respectively. The clustering method was quite stable: the proportion of patients staying in one cluster after resampling and reclustering was 97.4% (95% confidence interval [CI]: 85.6-99.9%). These clusters characterized groups of patients with different functional outcomes: from mild to severe, 12%, 19%, 36%, and 58% of patients had unfavorable 6 month outcome. Compared with the mild and the upper intermediate cluster, the lower intermediate and the severe cluster received more key interventions. To conclude, four types of TBI patients may be defined by injury mechanism, presence of major extracranial injury and GCS. Describing patients according to these three characteristics could potentially capture differences in etiology and care pathways better than with GCS only.

Machine Learning to Predict In-Hospital Morbidity and Mortality after Traumatic Brain Injury

Recently, successful predictions using machine learning (ML) algorithms have been reported in various fields. However, in traumatic brain injury (TBI) cohorts, few studies have examined modern ML algorithms. To develop a simple ML model for TBI outcome prediction, we conducted a performance comparison of nine algorithms: ridge regression, least absolute shrinkage and selection operator (LASSO) regression, random forest, gradient boosting, extra trees, decision tree, Gaussian naïve Bayes, multi-nomial naïve Bayes, and support vector machine. Fourteen feasible parameters were introduced in the ML models, including age, Glasgow Coma Scale (GCS), systolic blood pressure (SBP), abnormal pupillary response, major extracranial injury, computed tomography (CT) findings, and routinely collected laboratory values (glucose, C-reactive protein [CRP], and fibrin/fibrinogen degradation products [FDP]). Data from 232 patients with TBI were randomly divided into a training sample (80%) for hyperparameter tuning and validation sample (20%). The bootstrap method was used for validation. Random forest demonstrated the best performance for in-hospital poor outcome prediction and ridge regression for in-hospital mortality prediction: the mean statistical measures were 100% sensitivity, 72.3% specificity, 91.7% accuracy, and 0.895 area under the receiver operating characteristic curve (AUC); and 88.4% sensitivity, 88.2% specificity, 88.6% accuracy, and 0.875 AUC, respectively. Based on the feature selection method using the tree-based ensemble algorithm, age, Glasgow Coma Scale, fibrin/fibrinogen degradation products, and glucose were identified as the most important prognostic factors for poor outcome and mortality. Our results indicate the relatively good predictive performance of modern ML for TBI outcome. Further external validation is required for more heterogeneous samples to confirm our results.

Divergent Six Month Functional Recovery Trajectories and Predictors after Traumatic Brain Injury: Novel Insights from the Citicoline Brain Injury Treatment Trial Study.

Cross-sectional approaches to outcome assessment may not adequately capture heterogeneity in recovery after traumatic brain injury (TBI). Using latent class mixed models (LCMM), a data-driven analytic that identifies groups of patients with similar trajectories, we identified distinct 6 month functional recovery trajectories in a large cohort (n = 1046) of adults 18-70 years of age with complicated mild to severe TBI who participated in the Citicoline Brain Injury Treatment Trial (COBRIT). We used multinomial logistic fixed effect models and backward elimination, forward selection, and forward stepwise selection with several stopping rules to explore baseline predictors of functional recovery trajectory. Based on statistical and clinical considerations, the seven-class model was deemed superior. Visualization of these seven functional recovery trajectories revealed that each trajectory class started at one of three recovery levels at 1 month, which, for ease of reference we labeled groups A-C: Group A, good recovery (two classes; A1 and A2); Group B, moderate disability (two classes; B1 and B2); and Group C, severe disability (three classes; C1, C2, and C3). By 6 months, these three groups experienced dramatically divergent trajectories. Group A experienced stable good recovery (A1, n = 115) or dramatic decline (A2, n = 4); Group B experienced rapid complete recovery (B1, n = 71) or gradual recovery (B2, n = 742); Group C experienced dramatic rapid recovery (C1, n = 12), no recovery (C2, n = 91), or death (C3, n = 11). Trajectory class membership was not predicted by citicoline treatment (p = 0.57). The models identified demographic, pre-injury, and injury-related predictors of functional recovery trajectory, including: age, race, education, pre-injury employment, pre-injury diabetes, pre-injury psychiatric disorder, site, Glasgow Coma Scale (GCS) score, post-traumatic amnesia, TBI mechanism, major extracranial injury, hemoglobin, and acute computed tomographic (CT) findings. GCS was the most consistently selected predictor across all models. All models also selected at least one demographic or pre-injury medical predictor. LCMM successfully identified dramatically divergent, clinically meaningful 6 month recovery trajectories with utility to inform clinical trial design.

Serum Amyloid A1 as a Potential Intracranial and Extracranial Clinical Severity Biomarker in Traumatic Brain Injury.

Extracranial injury is frequently present in patients with traumatic brain injury (TBI). However, no reliable biomarker exists nowadays to evaluate the magnitude and extension of extracranial injury as well as the identification of patients who are at risk of developing secondary injuries. The purpose of this study was to identify new possible peptide biomarkers by mass spectrometry analysis in patients with TBI and ascertain whether the novel biomarker discovered by peptide mass fingerprinting, serum amyloid A1 (SAA1), is capable of reflecting the condition of the patient and both intracranial and extracranial injury extension. Demographic characteristics, clinical data, and serum samples were prospectively collected from 120 patients with TBI (Glasgow Coma Scale [GCS] score 3-15) on admission. Biomarkers were quantified by enzyme-linked immunosorbent assay. Intracranial lesion volume was measured from the semiautomatic segmentation of hematoma on computed tomography (CT) using Analyze software. Functional outcome was evaluated using the Glasgow Outcome Scale (GOS) at hospital discharge and GOS extended scores at 6 months. The SAA1 levels were significantly associated with intracranial (GCS score at admission, lesion load measured with cranial CT, and pupil responsiveness) and extracranial clinical severity (all Abbreviated Injury Scale regions, Injury Severity Score, major extracranial injury, polytrauma, and orthopedic fractures presence), along with systemic secondary insults and functional outcome. SAA1 was is associated with the volume of traumatic intracranial lesions. The SAA1 levels were correlated with astroglial S100β and glial fibrillary acidic protein (GFAP), neuronal neuron-specific enolase (NSE), and axonal total tau (T-tau) and phosphorylated neurofilament heavy chain (pNF-H) injury markers. SAA1 predicts unfavorable outcome and mortality at hospital discharge (area under the curve [AUC] = 0.90, 0.82) and 6 months (AUC = 0.89). SAA1 can be established as a marker for the overall patient condition due to its involvement in the neuroendocrine axis of the systemic response to craniocerebral trauma.

Feasibility of Online Traumatic Brain Injury Prognostic Corticosteroids Randomisation After Significant Head Injury (CRASH) Model as a Predictor of Mortality

Traumatic brain injury (TBI) is a major cause of mortality in many countries. According to the World Health Organization, traffic crashes are a leading cause of death, with 1.25 million deaths worldwide in 2013. A 2013 global road safety report listed 68 low-to-middle income countries that had an increased mortality rate owing to traffic accidents. The aim of this study was to analyze feasibility of use of an online prognostic model from the Medical Research Council Corticosteroids Randomization After Significant Head Injury (CRASH) trial collaborators in our center. This is a cross-sectional retrospective study of 229 patients with TBI who were admitted to the Neurosurgery Unit at Dr. Hasan Sadikin Hospital, Bandung, from July to December2016. During the study period, 495 patients with TBI were admitted; 229 patients were included in the study. Several variables were analyzed using independent statistical methods before being included in the online CRASH calculator, including Glasgow Coma Scale score (P=0.000), pupillary reaction to light (P= 0.000), major extracranial injury (P= 0.002), and interval following incidence (P= 0.000). Statistical analysis showed that the online CRASH prognostic model reliably predicted 14-day mortality rate (P= 0.000) with 91.6% sensitivity and 95.1% specificity. The online CRASH model is a good prognostic model that can be used for patients with TBI in many developing countries.

Health State Preference Weights for the Glasgow Outcome Scale Following Traumatic Brain Injury: A Systematic Review and Mapping Study.

BackgroundValid and relevant estimates of health state preference weights (HSPWs) for Glasgow Outcome Scale (GOS) categories are a key input of economic models evaluating treatments for traumatic brain injury (TBI).ObjectivesTo characterize existing HSPW estimates, and model the EuroQol five-dimensional questionnaire (EQ-5D) from the GOS, to inform parameterization of future economic models.MethodsA systematic review of HSPWs for GOS categories following TBI was conducted using a highly sensitive search strategy implemented in an extensive range of information sources between 1975 and 2016. A cross-sectional mapping study of GOS health states onto the three-level EQ-5D UK tariff index values was also performed in patients with significant TBI (head region Abbreviated Injury Scale score ≥3) from the Victoria State Trauma Registry. A limited dependent variable mixture model was used to estimate the 12-month EQ-5D UK value set as a function of GOS category, age, and other explanatory variables.ResultsSix unique HSPWs from five eligible studies were identified. All studies were at high risk of bias with limited applicability. The magnitude of HSPWs differed significantly between studies. Three class mixture models demonstrated excellent goodness of fit to the observed Victoria State Trauma Registry data. GOS category, age at injury, sex, comorbidity, and major extracranial injury all had significant independent effects on mean EQ-5D utility values.ConclusionsThe few available HSPWs for GOS categories are challenged by potential biases and restricted generalizability. Mixture models are presented to provide HSPWs for GOS categories consistent with the National Institute for Health and Care Excellence reference case.

Models of Mortality Probability in Severe Traumatic Brain Injury: Results of the Modelling by the UK Trauma Registry

Currently available prognostic models in Traumatic Brain Injury (TBI) are derived from historical data sets or from heterogeneous data sets, depending upon the trauma care delivered. The objective of our study was to develop models to predict survival in a recent cohort of TBI patients within a relatively homogeneous trauma care system. Records of patients with brain injury were extracted from the Trauma Audit and Research Network (TARN) database. The relationship of the variables (i.e., age, Glasgow Coma Score [GCS], pupillary reactivity, Injury Severity Score [ISS], Computed Tomography [CT] classifications, classification of various intracranial pathologies, systolic and mean blood pressure, oxygen saturation, and the presence of extracranial injury) to survival at discharge were determined. Stepwise logistical regression analysis was performed to determine the best prognostic model. Two models were derived from data of 802 patients (models A and B). Age, GCS, pupillary reactivity, hypoxia, and brainstem injury are significant predictors in both. However, model A contains ISS in contrast to model B, which contains the presence of brain swelling and major extracranial injury instead. Both models have good predictive performance (model A: area under the Receiver Operating Characteristic [ROC] curve [AUC]=0.92 [95% CI, 0.90-0.95], Nagelkerke R(2), 0.62; model B: AUC=0.93 [95% CI: 0.91-0.95], Nagelkerke R(2): 0.63). Hence, two accurate and reliable prognostic models were developed from a recent cohort of the TBI population.

Factors correlating with delayed trauma center admission following traumatic brain injury.

BackgroundDelayed admission to appropriate care has been shown increase mortality following traumatic brain injury (TBI). We investigated factors associated with delayed admission to a hospital with neurosurgical expertise in a cohort of TBI patients in the intensive care unit (ICU).MethodsA retrospective analysis of all TBI patients treated in the ICUs of Helsinki University Central Hospital was carried out from 1.1.2009 to 31.12.2010. Patients were categorized into two groups: direct admission and delayed admission. Patients in the delayed admission group were initially transported to a local hospital without neurosurgical expertise before inter-transfer to the designated hospital. Multivariate logistic regression was utilized to identify pre-hospital factors associated with delayed admission.ResultsOf 431 included patients 65% of patients were in the direct admission groups and 35% in the delayed admission groups (median time to admission 1:07h, IQR 0:52–1:28 vs. 4:06h, IQR 2:53–5:43, p <0.001). In multivariate analysis factors increasing the likelihood of delayed admission were (OR, 95% CI): male gender (3.82, 1.60-9.13), incident at public place compared to home (0.26, 0.11-0.61), high energy trauma (0.05, 0.01-0.28), pre-hospital physician consultation (0.15, 0.06-0.39) or presence (0.08, 0.03-0.22), hypotension (0.09, 0.01-0.93), major extra cranial injury (0.17, 0.05-0.55), abnormal pupillary light reflex (0.26, 0.09-0.73) and severe alcohol intoxication (12.44, 2.14-72.38). A significant larger proportion of patients in the delayed admission group required acute craniotomy for mass lesion when admitted to the neurosurgical hospital (57%, 21%, p< 0.001). No significant difference in 6-month mortality was noted between the groups (p= 0.814).ConclusionDelayed trauma center admission following TBI is common. Factors increasing likelihood of this were: male gender, incident at public place compared to home, low energy trauma, absence of pre-hospital physician involvement, stable blood pressure, no major extra cranial injuries, normal pupillary light reflex and severe alcohol intoxication. Focused educational efforts and access to physician consultation may help expedite access to appropriate care in TBI patients.

Predicting intracranial hemorrhage after traumatic brain injury in low and middle-income countries: A prognostic model based on a large, multi-center, international cohort

BackgroundTraumatic brain injury (TBI) affects approximately 10 million people annually, of which intracranial hemorrhage is a devastating sequelae, occurring in one-third to half of cases. Patients in low and middle-income countries (LMIC) are twice as likely to die following TBI as compared to those in high-income countries. Diagnostic capabilities and treatment options for intracranial hemorrhage are limited in LMIC as there are fewer computed tomography (CT) scanners and neurosurgeons per patient as in high-income countries.MethodsThe Medical Research Council CRASH-1 trial was utilized to build this model. The study cohort included all patients from LMIC who received a CT scan of the brain (n = 5669). Prognostic variables investigated included age, sex, time from injury to randomization, pupil reactivity, cause of injury, seizure and the presence of major extracranial injury.ResultsThere were five predictors that were included in the final model; age, Glasgow Coma Scale, pupil reactivity, the presence of a major extracranial injury and time from injury to presentation. The model demonstrated good discrimination and excellent calibration (c-statistic 0.71). A simplified risk score was created for clinical settings to estimate the percentage risk of intracranial hemorrhage among TBI patients.ConclusionSimple prognostic models can be used in LMIC to estimate the risk of intracranial hemorrhage among TBI patients. Combined with clinical judgment this may facilitate risk stratification, rapid transfer to higher levels of care and treatment in resource-poor settings.

OP24 Assessing the Cost-Effectiveness of Alternative Care Pathways: A Case Study Evaluating Early Transfer to Neuroscience Centres for Critically ill Patients with Acute Traumatic Brain Injury

BackgroundAcute traumatic brain injury (TBI) is a major cause of death, disability and cost. For critically-ill adult TBI patients who present outside a neuroscience centre, and do not require neurosurgery,...

Prognostic Value of Major Extracranial Injury in Traumatic Brain Injury

Major extracranial injury (MEI) is common in traumatic brain injury (TBI) patients, but the effect on outcome is controversial. To assess the prognostic value of MEI on mortality after TBI in an individual patient data meta-analysis of 3 observational TBI studies (International Mission on Prognosis and Clinical Trial Design in TBI [IMPACT]), a randomized controlled trial (Corticosteroid Randomization After Significant Head Injury [CRASH]), and a trauma registry (Trauma Audit and Research Network [TARN]). MEI (extracranial injury with an Abbreviated Injury Scale ≥ 3 or requiring hospital admission) was related to mortality with logistic regression analysis, adjusted for age, Glasgow Coma Scale motor score, and pupil reactivity and stratified by TBI severity. We pooled odds ratios (ORs) with random-effects meta-analysis. We included 39,274 patients. Mortality was 25%, and 32% had MEI. MEI was a strong predictor for mortality in TARN, with adjusted odds ratios of 2.81 (95% confidence interval [CI], 2.44-3.23) in mild, 2.18 (95% CI, 1.80-2.65) in moderate, and 2.14 (95% CI, 1.95-2.35) in severe TBI patients. The prognostic effect was smaller in IMPACT and CRASH, with pooled adjusted odds ratios of 2.14 (95% CI, 0.93-4.91) in mild, 1.46 (95% CI, 1.14-1.85) in moderate, and 1.18 (95% CI, 1.03-1.55) in severe TBI. When patients who died within 6 hours after injury were excluded from TARN, the effect of MEI was comparable with IMPACT and CRASH. MEI is an important prognostic factor for mortality in TBI patients. However, the effect varies by population, which explains the controversy in the literature. The strength of the effect is smaller in patients with more severe brain injury and depends on time of inclusion in a study.

Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients

Objective To develop and validate practical prognostic models for death at 14 days and for death or severe disability six months after traumatic brain injury.Design Multivariable logistic regression to select...